1. Field of the Invention
The present invention relates to an image segmentation threshold value deciding method, an image sensing system, a gesture determining method, and a gesture determining system, and particularly relates to an image sensing system, a gesture determining method, and a gesture determining system which can dynamically adjust the image segmentation threshold value.
2. Description of the Prior Art
More and more electronic apparatuses can perform different functions according to a user's gestures (ex. a smart phone and a smart TV). However, if it is desired to correctly detect a gesture, a location for a hand must be detected before performing such operation. Generally, if a depth sensor is not provided, image segmentation should be firstly performed to determine a hand image from images captured by the image sensor. A common image segmentation method is performed based on brightness.
FIG. 1A and FIG. 1B are schematic diagrams illustrating a prior art operation for performing image segmentation to an image according to brightness. As illustrated in FIG. 1A, the sensing image Img captured by the image sensor comprises a hand image Img_h and a background image Img_b. Also, in FIG. 1B, image segmentation has been performed to the sensing image Img, thus a segmented image Img_s is generated. A common image segmentation method gives a higher brightness (ex. a grey level 255) to at least part for a sensing image, if the part for a sensing image is higher than an image segmentation threshold value. Oppositely, the common image segmentation method gives a lower brightness (ex. a grey level 0) to at least part for a sensing image, if the part for a sensing image is lower than the image segmentation threshold value. As illustrated in FIG. 1B, after image segmentation, the segmented hand image Img_hs in the segmented image Img_s has a higher brightness, and the segmented background image Img_bs has a lower brightness. Accordingly, the hand image can be correctly determined after the sensing image is segmented.
However, the methods in FIG. 1A and FIG. 1B may generate an incorrect segmented hand image under some situations. FIG. 2A and FIG. 2B are schematic diagrams illustrating that the background image has interference while conventional image segmentation is performed according to brightness. As illustrated in FIG. 2A, the sensing image Img captured by the image sensor comprises a hand image Img_h and a background image Img_b. Also, the background image Img_b further comprises an object image Img_o, which has brightness close to brightness of the hand image Img_h. Accordingly, in FIG. 2B, the segmented hand image Img_hs and the segmented object image Img_os have the same brightness. For such case, the size and the location of the hand image may be mis-determined.
Besides FIG. 2A and FIG. 2B, the methods in FIG. 1A and FIG. 1B may have the above-mentioned fragile hand issue. FIG. 3 is a schematic diagram illustrating that a fragile hand image is generated while conventional image segmentation is performed according to brightness. FIG. 3 can be acquired via performing image segmentation to FIG. 1A. However, the segmented hand image Img_hs may become an incomplete image due to an unsuitable threshold value or interference of environment light. For such case, the size and the location of the hand image may also be mis-determined.